Nevertheless, the signals restored after decoding are no longer identical to the original signals. The constraints imposed in terms of data rate or bandwidth available for transmission and the content of the signal imply that characteristic kinds of degradation appear at low data rate or under difficult transmission conditions.
In order to monitor signal quality, most measuring methods need to compare received signals (or characteristics of such signals) with transmitted signals (or with characteristics of transmitted signals). Consequently, a prior condition for monitoring quality is to be able to achieve accurate time synchronization between the signals that are to be compared.
Various methods exist for achieving for time synchronization between any two digital signals, referred to as E and S. Also such methods seek to establish correspondence between elements, i.e. portions, of said signals. For example, when synchronizing video sequences, the basic element might be one image; similarly, for an audio sequence, it could be one sample.
Existing methods can be classified in three approaches.
The most usual approach implements correlation on complete decoded signals. It consists in comparing the two signals E and S for synchronization on the basis of their respective contents. Assuming that the content of the signals varies significantly between two consecutive elements, a comparison between the signals E and S shows a high degree of similarity between the signals only when the elements thereof are in correspondence. In all other cases, the similarity that is observed is much smaller.
One example of an application of that principle to animated images consists in evaluating the variance of the error image E-S, which passes through a minimum when the images in the two video sequences are in correspondence. Alternatively, correlation between the two images is established using equation (2) below. Each pixel occupying the same spatial position (x,y) in the images of the two sequences Γ(τ) is at a maximum when the signals are time synchronized. The parameter τ gives the time offset for applying to one of the signals in order to obtain synchronization. An equation similar to equation (1) is applicable to audio signals.
                              Γ          ⁡                      (            τ            )                          =                              ∑                          t              =              0                                      T              -              1                                ⁢                                          ⁢                                    E              ⁡                              (                t                )                                      ·                          S              ⁡                              (                                  t                  -                  τ                                )                                                                        (        1        )            where T is an arbitrary duration.
                                          Γ            ⁡                          (              τ              )                                =                                    ∑                              t                =                0                                            T                -                1                                      ⁢                                          ∑                                  x                  =                  0                                                  M                  -                  1                                            ⁢                                                          ⁢                                                ∑                                      y                    =                    0                                                        N                    -                    1                                                  ⁢                                                      E                    ⁡                                          (                                              x                        ,                        y                        ,                        t                                            )                                                        ·                                      S                    ⁡                                          (                                              x                        ,                        y                        ,                                                  t                          -                          τ                                                                    )                                                                                                          ,                            (        2        )            where (M, N) is the size of an image in E and S.
For more effective correlation, the signals E and S can initially be normalized:
                              E          ⁡                      (            t            )                          =                                            E              ⁡                              (                t                )                                      -                          mean              ⁢                                                          [                              E                ⁡                                  (                  t                  )                                            ]                                                                          ∑                                  i                  =                  0                                                  T                  -                  1                                            ⁢                                                          ⁢                                                E                  2                                ⁡                                  (                  t                  )                                                                                        (        3        )            where mean (E) is the average of E over the interval T.
The main drawback of that type of method is the need for content that varies significantly on a continuous basis. Depending on the type of signal being analyzed, that assumption is not always true. The content of the signals therefore has a direct influence on the performance of the method. Furthermore, the method can be difficult to implement in terms of computation power, particularly when it is applied to two video signals or to two long periods of audio signal. Furthermore, in order to use that type of approach on complete decoded signals, it is necessary for both signals E and S to be available at the same point: this is a major constraint which cannot always be satisfied in certain applications such as monitoring the quality of digital television signals in an operational system.
A second known approach uses synchronization by time references.
This second class of methods makes use of the possible presence of time references (RT) in the signals. When these time references are associated with perceptible or useful content in the signals (encoded sound or images), it is possible to make use of them when synchronizing two signals.
For this purpose, the process is based only on two series of time references RT, which are extracted from the signals using some appropriate extraction method. The time references RT can be constituted, for example, by numbers whose values increase over time, with synchronization being performed merely by selecting, for each time reference RT in a sequence, the closest time reference in the series from the other sequence.
Nevertheless, the use of reduced data rate digital systems, in particular for digital television signals, gives rise to specific problems which prevent accurate synchronization being achieved between two decoded signals in real time. The digital transmission system and the multiple pieces of equipment through which the signal passes (coder, multiplexer, transmultiplexer, decoder) lie behind this.
In a digital decoder (PDEC), an internal clock giving the rate at which decoded signal elements are output is generated on the basis of time references (RT) present in the encoded binary stream (FB). However, only the output frequency of the signals is servo-controlled on the time references, and phase is not servo-controlled. Consequently, there exists a phase offset φ between a given series of time references RT and the decoded signals (FIG. 2). The phase offset is due to the digital memories present in the decoder.
This phase offset φ is constant so long as the stream is not interrupted, but its value changes if there is a change in decoder, or in the binary stream, or even if the binary stream is merely interrupted and then taken up again. The value of the phase offset can be of an order of magnitude that is not less than the duration of the longest element in the signal. For example, when the decoded signals contain video (FIG. 2), the phase offset can be of several images.
The existence of a phase offset between the time references and the signals E and S output by datarate-reducing digital decoders has an impact on the performance of synchronization using time references. The two associated series of time references RTE and RTS are phase offset from E and S by φE and φS respectively. Furthermore, φE and φS are unknown. The two series of time references RTE and RTS are thus phase shifted by a value that is unknown, which can be of the order of several video images. Consequently, synchronizing E and S on the basis solely of time references is approximate. This approach does not enable synchronization to be obtained to within one signal element.
This approach presents the drawback of precision that is limited firstly by the precision concerning the values of the time references RT, and secondly by the need for these references to be transmitted synchronously with perceptible or useful content in the signals. Furthermore, when used with datarate-reducing digital systems, it provides coarse synchronization only. However, it is very simple to implement.
A third class of synchronization methods seeks to mitigate the need for significant and continuous variation in signal content in order to obtain good performance with correlation methods. To do this, it is possible to modify signal content so as to insert specific information therein for the purpose of optimizing correlation reliability. One possibility is to insert special patterns into the images.
That approach thus corrects a defect of correlation approaches, but it introduces signal modification, and that represents a major constraint that is incompatible with numerous applications, including monitoring the quality of digital television signals in an operational system.